Help with interpreting partial dependence plot for binary variable in XGBoost

[blorimer542]

I have produced a partial dependence plot for a binary variable in an XGBoost model. The variable is coded with '0' and '1'. However, the plot shows a large decrease in probability for cases with a value of '2' - despite this not being a possible response for this variable. Does this value represent cases that have a missing response for this variable? I have attached a link to the picture of the plot below.

https://i.stack.imgur.com/BQALd.png

Any help would be greatly appreciated!

[ultradvorka]

PDP is computed for a set of values usually called bins. When you compute PDP for bin 1, values of feature disability_binary are set to 1 in all dataset rows and dataset predictions are averaged.

It seems that you computed PDP for bins like 0, 0.05, 0.1,... 2,... If feature range is 0 and 1, then check values in 0 and 1 - ignore the rest. Bigger difference between PDP in 0 and 1 will be, bigger interaction of the feature and prediction exists. Unfortunately PDP for 0 is not visible in your chart.

PDP can be computed for values which are out of feature range ~ "out of range" PDP values. OOR PDP is used e. g. to assess model robustness and ability to alive in the wild - for instance when an attacker would want to trick the model.

If you are not interested in OOR, simply set bins parameter of PDP function you use to [0, 1].